Pith. sign in

REVIEW 3 major objections 3 minor 1 cited by

Reconstructing chemical enrichment pathways in disc galaxies: A phylogenetic approach

T0 review · 3 major / 3 minor · reviewed 2026-07-12 · grok-4.5

Pith's one-line read Phylogenetic trees of stellar chemistry recover distinct enrichment pathways that track how different regions of a disc galaxy assembled.

desk verdict Promising methods paper on chemical phylogenetics for disc assembly, but we only have the abstract and the load-bearing claim (tree topology = assembly pathway) is still unaudited. read the letter →

arxiv 2604.11974 v2 pith:C4CFWCY5 submitted 2026-04-13 astro-ph.GA

classification astro-ph.GA
keywords galacticphylogeneticschemicalenrichmentdiscgalaxiesstellarpopulationsCorrectedCollessindexbar-driveninflowsspiralarmsabundances
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper argues that methods borrowed from evolutionary biology can read a galaxy’s chemical fossil record. Using a high-resolution simulation of an isolated disc, the authors build phylogenetic trees from the chemical abundances of stars in an inner ring (shaped by early bar-driven inflows) and an outer ring (shaped by spiral arms). The trees look different: the inner region shows a tight early clade dominated by rapid core-collapse supernova enrichment, then a hierarchical climb as Type Ia supernovae and AGB stars contribute; the outer region produces more balanced, caterpillar-like trees with smoother abundance gradients. A standard tree-balance metric, the Corrected Colless index, separates the two regions and remains stable even with only about a hundred stars. If the method works, chemical phylogenetics becomes a practical way to reconstruct assembly history from abundance patterns rather than from kinematics alone.

What carries the argument

Galactic phylogenetic trees built from multi-element chemical abundance vectors of selected stellar populations, quantified by the Corrected Colless index of tree balance, which turns abundance relationships into a readable map of enrichment order and mixing.

What would settle it

Apply the same tree construction and Corrected Colless comparison to stars drawn from inner and outer rings of an independent simulation (or real survey fields) with known but different bar versus spiral assembly histories; if the index no longer separates the regions or the SNII-then-SNIa hierarchy disappears, the claim fails.

Watch

Extended reading notes

Core claim

In a simulated disc galaxy, phylogenetic trees constructed from stellar chemical abundances recover region-dependent enrichment pathways: the inner ring forms a compact old SNII-dominated clade followed by hierarchical SNIa/AGB enrichment, while the outer ring yields more symmetric trees consistent with prolonged star formation and local mixing, and these structural differences are captured by the Corrected Colless index even for modest samples.

Load-bearing premise

Tree shape built from chemical abundance vectors of selected stars truly records assembly history rather than simulation mixing, particle selection, or the particular enrichment model.

Editorial extensions

If this is right

  • Inner-disc versus outer-disc stellar samples should produce measurably different phylogenetic balance even when only ~100 stars are available.
  • Chemical phylogenetics can complement kinematic archaeology by ordering enrichment events without requiring full orbital histories.
  • Rapid early SNII clades followed by hierarchical SNIa/AGB branches become an expected chemical signature of bar-driven central assembly.
  • Smoother, more symmetric trees become an expected signature of spiral-arm-dominated outer discs with efficient local mixing.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • If the method is robust, multi-element abundance catalogues from large spectroscopic surveys could be turned into assembly chronologies for real Milky Way-like discs without new simulations for every field.
  • Tree-balance metrics may offer a compact scalar diagnostic for comparing chemical evolution across different galaxy simulations and enrichment codes.
  • The same residual-structure idea could be stress-tested on galaxies that experienced major mergers to see whether the balance signal survives violent mixing.
Share X Bluesky LinkedIn Reddit HN

Signed reviews

No signed human review yet.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 3 minor

Summary. The manuscript (as represented by its abstract and metadata for arXiv:2604.11974) proposes applying phylogenetic tree reconstruction to chemical abundance vectors of stellar populations in a high-resolution isolated disc-galaxy simulation, in order to recover assembly-linked chemical enrichment pathways. Two radial regions are contrasted: an inner ring associated with early bar-driven inflows and an outer ring shaped by spiral arms. Trees are quantified with the Corrected Colless balance index; the abstract reports a compact old SNII-dominated clade plus hierarchical SNIa/AGB enrichment in the inner ring, versus more symmetric caterpillar-like trees and smoother gradients in the outer ring, with enrichment-rate trends offered as corroboration and index differences said to converge for modest samples (NSSP = 100). The central claim is that galactic phylogenetics is a novel, complementary tool for decoding the chemical fossil record of disc assembly.

Significance. If the method robustly recovers assembly-driven enrichment structure beyond what is already visible in abundance gradients and enrichment-rate histories, it would be a genuine methodological contribution to galactic archaeology, importing a mature biological toolkit (tree balance metrics, clade structure) into chemical evolution. The abstract’s emphasis on multi-channel enrichment (SNII, SNIa, AGB), particle inheritance of parent-gas composition, and sample-size convergence (NSSP = 100) is in principle falsifiable and of practical interest for both simulations and future multi-element surveys. That significance, however, is entirely conditional on controls that cannot be audited from the materials provided for this review.

major comments (3)
  1. The full manuscript text supplied under paper_id 2604.11974 is not this paper: it is an unrelated DeepONet / coherent nonlinear wave dynamics manuscript (arXiv:2604.11972). No methods, distance metric, tree-building algorithm, figures, tables, or statistical tests for the galactic phylogenetics work are available. A load-bearing technical review of the central claim is therefore impossible; the report below is constrained to the abstract and cannot verify any result.
  2. Abstract (central claim): Differences in phylogenetic topology and Corrected Colless index between the inner (bar-influenced) and outer (spiral-influenced) rings are interpreted as recovering assembly-linked enrichment pathways. That inference requires that abundance-vector trees primarily encode assembly history rather than continuous mixing, radial enrichment-rate gradients, particle selection, chemical-distance definition, or the isolated-disc enrichment model. The abstract supplies no distance metric, linkage/algorithm, null models (e.g. shuffled abundances, mixed-region controls, or trees built from enrichment rates alone), or comparison showing that phylogeny adds information beyond the enrichment-rate corroboration already cited. Until those controls are present and auditable, the assembly-history reading of tree structure remains an assumption.
  3. Abstract (experimental design): Results rest on a single isolated disc simulation and two hand-chosen rings. Without a suite of simulations (varying bar strength, spiral structure, feedback, or cosmological accretion) or explicit tests against known assembly histories, it is unclear whether tree-balance differences generalise or are simulation- and selection-specific. The free parameter NSSP and the claim of robust convergence at NSSP = 100 also cannot be assessed without the sampling protocol and uncertainty quantification.
minor comments (3)
  1. Abstract: ‘Target particles are selected to store the chemical history of each chemical element’ is ambiguous (which elements, how many, abundance ratios vs absolute abundances, normalisation). Clarify in any resubmission.
  2. Abstract: ‘caterpillar-like trees’ and ‘compact clade’ are qualitative; define operationally (e.g. Colless, Sackin, or clade-size statistics) when the correct full text is provided.
  3. Title/abstract framing as ‘unveil assembly histories’ is stronger than what an isolated disc (no mergers/accretion) can demonstrate; consider ‘enrichment pathways linked to internal secular structure’ unless cosmological assembly is actually modelled.

Circularity Check

0 steps flagged · score 0.0 of 10

No circularity: empirical phylogenetic comparison of simulated chemical abundances, not a closed-loop derivation.

full rationale

Based on the available abstract (the cached full manuscript is the unrelated DeepONet paper 2604.11972, so methods/equations cannot be audited), the work is an empirical simulation experiment: stellar particles inherit parent-gas chemical compositions; phylogenetic trees are built for inner-ring vs outer-ring populations; tree balance is quantified with the Corrected Colless index; and chemical enrichment rates are used as independent corroboration. Nothing in the abstract defines the claimed pathway difference (compact SNII clade vs caterpillar-like outer trees; significant Colless contrast) as equal to a fitted parameter or as a tautology of the inputs. There is no self-definitional loop, no fitted quantity re-labeled as a prediction, no load-bearing uniqueness theorem imported from the authors, and no ansatz smuggled via self-citation. Residual methodological risks (region selection, chemical distance, enrichment model) are assumptions about interpretation, not circular reductions of the derivation chain. Score 0 is therefore the honest finding from the text that can be quoted.

Assumptions & free parameters 1 free parameters · 4 assumptions · 1 invented entities

With only the abstract, the load-bearing premises are domain assumptions of chemical tagging and phylogenetic reconstruction plus simulation-specific modeling choices. No free numerical parameters beyond the reported sample size threshold are given; invented entities are methodological constructs (galactic phylogenetic trees of stellar populations), not new physical particles.

free parameters (1)
  • NSSP (number of stellar sample particles) = 100
    Abstract reports robust convergence at NSSP = 100; this is a chosen sample size that affects claimed stability of tree indices.
assumptions (4)
  • domain assumption Stellar chemical abundance vectors inherit parent-gas composition and preserve enough evolutionary signal to reconstruct enrichment pathways via phylogenetic trees.
    Core premise of galactic chemical tagging and of the phylogenetic application stated in the abstract.
  • domain assumption The Corrected Colless index of tree balance is a meaningful discriminator of chemical assembly modes between galactic regions.
    Abstract uses this biological metric as the quantitative structural comparison between inner and outer rings.
  • ad hoc to paper An isolated high-resolution disc simulation with multi-channel enrichment (SNII, SNIa, AGB) is a sufficient laboratory for testing whether phylogenetics can unveil assembly histories.
    Study design rests on one simulated isolated disc and two selected rings; no multi-simulation or observational validation is stated in the abstract.
  • domain assumption Inner-ring chemistry is dominated by early bar-driven inflows and outer-ring chemistry by spiral-arm-driven prolonged star formation and local mixing.
    Abstract interprets tree differences through these dynamical narratives of the two regions.
invented entities (1)
  • Galactic phylogenetic trees of stellar populations (chemical clades)
    purpose: Represent hierarchical chemical enrichment relationships among stars as evolutionary trees analogous to biological phylogenies.
    The paper's central construct; independent evidence would require recovery of known assembly events in controlled simulations or real multi-element surveys beyond this abstract.

how reviews work

0 comments
Cite this review

Pith. "Pith review of Reconstructing chemical enrichment pathways in disc galaxies: A phylogenetic approach." pith.science (2026). https://pith.science/paper/C4CFWCY5

@misc{pith2026260411974,
  author       = {Pith},
  title        = {Pith review of: Reconstructing chemical enrichment pathways in disc galaxies: A phylogenetic approach},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/C4CFWCY5}},
  note         = {Machine review of arXiv:2604.11974}
}
read the original abstract

Phylogenetic methods, traditionally used in biology to trace the evolutionary relationships among species, are emerging as a powerful framework to reconstruct evolutionary processes in galaxies from chemical information. We apply galactic phylogenetics to study the chemical evolution of stellar populations in distinct regions of a simulated disc galaxy, assessing its capability to unveil assembly histories. We used a high-resolution simulation that follows the chemical enrichment of an isolated disc galaxy, by different stellar progenitors. We track gas particles as they turn into stars and inherit their parent gas chemical composition. Target particles are selected to store the chemical history of each chemical element considered in the simulation. Two regions were analysed: an inner ring, influenced by early bar-driven inflows, and an outer ring, shaped by spiral arms. We built phylogenetic trees for stellar populations in each region and quantified their structure using the Corrected Colless index, a standard metric of tree balance used in biology. The inner ring tree reveals a compact clade of old stars enriched by rapid SNII feedback, followed by a hierarchical sequence with increasing SNIa and AGB contributions. In contrast, the outer ring exhibits more symmetric, caterpillar-like trees with smoother abundance gradients, consistent with more prolonged star formation and efficient local mixing. Chemical enrichment rates corroborate these trends, showing fast early enrichment in the inner ring and gradual, spatially extended enrichment in the outer disc. The structural indices differ significantly between the two regions and converge robustly even for modest stellar samples (NSSP = 100). Galactic phylogenetics provides a novel and complementary tool to decode the fossil record of galaxies.

Figures

Figures reproduced from arXiv: 2604.11974 by the authors.

Figure 1
Figure 1. Face-on and edge-on projected gas (left) and stellar (right) density distribution of the simulated galaxy. The inner, [PITH_FULL_IMAGE:figures/full_fig_p004_1.png] view at source ↗
Figure 2
Figure 2. Time evolution of the star formation rate for the whole [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗
Figure 3
Figure 3. Enrichment histories of target gas particles in the in [PITH_FULL_IMAGE:figures/full_fig_p006_3.png] view at source ↗
Figures from the paper (8 more)
Figure 4
Figure 4. Figure 4: The age-metallicity relation (AMR) of the stellar populations in the inner ring (purple squares) and outer ring (orange [PITH_FULL_IMAGE:figures/full_fig_p007_4.png]
Figure 5
Figure 5. Figure 5: Upper panel: Histogram of the radii of the donor parti [PITH_FULL_IMAGE:figures/full_fig_p007_5.png]
Figure 6
Figure 6. Figure 6: Phylogenetic tree constructed with 400 target stellar particles randomly selected from the inner ring. Color indicates the age [PITH_FULL_IMAGE:figures/full_fig_p009_6.png]
Figure 7
Figure 7. Figure 7: Same as Fig [PITH_FULL_IMAGE:figures/full_fig_p009_7.png]
Figure 8
Figure 8. Figure 8: Phylogenetic Tree of the inner ring (same as in Fig. [PITH_FULL_IMAGE:figures/full_fig_p010_8.png]
Figure 9
Figure 9. Figure 9: Phylogenetic Tree of the outer ring (same as in Fig. [PITH_FULL_IMAGE:figures/full_fig_p010_9.png]
Figure 10
Figure 10. Figure 10: Distribution of tree balance metric, the CC index, com [PITH_FULL_IMAGE:figures/full_fig_p011_10.png]
Figure 11
Figure 11. Figure 11: Convergence of CC tree shape index, as a function [PITH_FULL_IMAGE:figures/full_fig_p011_11.png]

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Disentangling chemical evolution histories with phylogenetic trees

    astro-ph.GA 2026-06 unverdicted novelty 7.0 of 10

    Phylogenetic trees built from flexCE model abundances separate primarily by the outflow mass-loading parameter η, with branches connecting at the most metal-rich tips.

Reference graph

Works this paper leans on

73 extracted references · cited by 1 Pith paper

  1. [1]

    , " * write output.state after.block = add.period write newline

    ENTRY address archiveprefix author booktitle chapter edition editor howpublished institution eprint journal key month note number organization pages publisher school series title type volume year label extra.label sort.label short.list INTEGERS output.state before.all mid.sentence after.sentence after.block FUNCTION init.state.consts #0 'before.all := #1 ...

  2. [2]

    write newline

    " write newline "" before.all 'output.state := FUNCTION n.dashify 't := "" t empty not t #1 #1 substring "-" = t #1 #2 substring "--" = not "--" * t #2 global.max substring 't := t #1 #1 substring "-" = "-" * t #2 global.max substring 't := while if t #1 #1 substring * t #2 global.max substring 't := if while FUNCTION word.in bbl.in " " * FUNCTION format....

  3. [3]

    C., Somerville , R

    Arrigoni , M., Trager , S. C., Somerville , R. S., & Gibson , B. K. 2010, , 402, 173

  4. [4]

    A., Wetzel , A., Loebman , S

    Bellardini , M. A., Wetzel , A., Loebman , S. R., et al. 2021, , 505, 4586

  5. [5]

    & Freeman , K

    Bland-Hawthorn , J. & Freeman , K. C. 2003, in Astronomical Society of the Pacific Conference Series, Vol. 297, Star Formation Through Time, ed. E. Perez, R. M. Gonzalez Delgado, & G. Tenorio-Tagle , 457--+

  6. [6]

    & Menci , N

    Calura , F. & Menci , N. 2009, , 400, 1347

  7. [7]

    B., Padilla , N., et al

    Casanueva-Villarreal , C., Tissera , P. B., Padilla , N., et al. 2024, , 688, A183

  8. [8]

    E., Tissera , P

    Cataldi , P., Pedrosa , S. E., Tissera , P. B., et al. 2023, , 523, 1919

Show all 73 references
  1. [9]

    1997, ApJ, 477, 765

    Chiappini , C., Matteucci , F., & Gratton , R. 1997, ApJ, 477, 765

  2. [10]

    1859, On the Origin of Species by Means of Natural Selection (London: John Murray)

    Darwin, C. 1859, On the Origin of Species by Means of Natural Selection (London: John Murray)

  3. [11]

    B., et al

    de Brito Silva , D., Jofr \'e , P., Tissera , P. B., et al. 2024, , 962, 154

  4. [12]

    E., Bower , R

    De Rossi , M. E., Bower , R. G., Font , A. S., Schaye , J., & Theuns , T. 2017, , 472, 3354

  5. [13]

    Deason , A. J. & Belokurov , V. 2024, , 99, 101706

  6. [14]

    L., & Wicke, K

    Fischer, M., Herbst, L., Kersting, S., K \"u hn, A. L., & Wicke, K. 2023

  7. [15]

    Fragkoudi , F., Grand , R. J. J., Pakmor , R., et al. 2020, , 494, 5936

  8. [16]

    M., Torrey , P., Hemler , Z

    Garcia , A. M., Torrey , P., Hemler , Z. S., et al. 2023, , 519, 4716

  9. [17]

    2006, Molecular Biology and Evolution, 23, 1997

    Gascuel , O. 2006, Molecular Biology and Evolution, 23, 1997

  10. [18]

    B., Monachesi , A., et al

    Gonzalez-Jara , J., Tissera , P. B., Monachesi , A., et al. 2025, , 693, A282

  11. [19]

    & Madau , P

    Haardt , F. & Madau , P. 2001, in Clusters of Galaxies and the High Redshift Universe Observed in X-rays, ed. D. M. Neumann & J. T. V. Tran

  12. [20]

    Heard, S. B. 1992, Evolution, 46, 1818

  13. [21]

    2020, , 58, 205

    Helmi , A. 2020, , 58, 205

  14. [22]

    S., Torrey , P., Qi , J., et al

    Hemler , Z. S., Torrey , P., Qi , J., et al. 2021, , 506, 3024

  15. [23]

    1990, , 356, 359

    Hernquist , L. 1990, , 356, 359

  16. [24]

    1999, ApJS, 125, 439

    Iwamoto , K., Brachwitz , F., Nomoto , K., et al. 1999, ApJS, 125, 439

  17. [25]

    2021, , 502, 32

    Jackson , H., Jofr \'e , P., Yaxley , K., et al. 2021, , 502, 32

  18. [26]

    B., Sillero , E., et al

    Jara-Ferreira , F., Tissera , P. B., Sillero , E., et al. 2024, , 530, 1369

  19. [27]

    B., & Matteucci , F

    Jim \'e nez , N., Tissera , P. B., & Matteucci , F. 2015, , 810, 137

  20. [28]

    2025, , 699, A291

    Jofr \'e , P., Aguilera-G \'o mez , C., Villarreal , P., et al. 2025, , 699, A291

  21. [29]

    2017, , 467, 1140

    Jofr \'e , P., Das , P., Bertranpetit , J., & Foley , R. 2017, , 467, 1140

  22. [30]

    W., Weinberg , D

    Johnson , J. W., Weinberg , D. H., Vincenzo , F., et al. 2021, , 508, 4484

  23. [31]

    Karakas , A. I. 2010, , 403, 1413

  24. [32]

    J., Rupke , D., Zahid , H

    Kewley , L. J., Rupke , D., Zahid , H. J., Geller , M. J., & Barton , E. J. 2010, ApJL, 721, L48

  25. [33]

    & Slatkin, M

    Kirxpatrick, M. & Slatkin, M. 1993, Evolution, 47, 1171

  26. [34]

    A., & Mendel , J

    Leaman , R., VandenBerg , D. A., & Mendel , J. T. 2013, , 436, 122

  27. [35]

    2002, MNRAS, 330, 821

    Lia , C., Portinari , L., & Carraro , G. 2002, MNRAS, 330, 821

  28. [36]

    F., Wetzel , A

    Ma , X., Hopkins , P. F., Wetzel , A. R., et al. 2017, , 467, 2430

  29. [37]

    2021, , 29, 5

    Matteucci , F. 2021, , 29, 5

  30. [38]

    & Greggio , L

    Matteucci , F. & Greggio , L. 1986, A & A, 154, 279

  31. [39]

    & Ferrini , F

    Moll\'a , M. & Ferrini , F. 1995, ApJ, 454, 726

  32. [40]

    B., Tissera , P

    Mosconi , M. B., Tissera , P. B., Lambas , D. G., & Cora , S. A. 2001, , 325, 34

  33. [41]

    G., Okamoto , T., et al

    Nagashima , M., Lacey , C. G., Okamoto , T., et al. 2005, , 363, L31

  34. [42]

    F., Frenk , C

    Navarro , J. F., Frenk , C. S., & White , S. D. M. 1996, , 462, 563

  35. [43]

    F., Frenk , C

    Navarro , J. F., Frenk , C. S., & White , S. D. M. 1997, , 490, 493

  36. [44]

    E., Christensen-Dalsgaard , J., Mosumgaard , J

    Nissen , P. E., Christensen-Dalsgaard , J., Mosumgaard , J. R., et al. 2020, , 640, A81

  37. [45]

    2013, , 51, 457

    Nomoto , K., Kobayashi , C., & Tominaga , N. 2013, , 51, 457

  38. [46]

    A., Spitoni , E., Recio-Blanco , A., et al

    Palicio , P. A., Spitoni , E., Recio-Blanco , A., et al. 2023, , 678, A61

  39. [47]

    Pedrosa , S. E. & Tissera , P. B. 2015, , 584, A43

  40. [48]

    Perez , J., Michel-Dansac , L., & Tissera , P. B. 2011, MNRAS, 417, 580

  41. [49]

    & Matteucci , F

    Pipino , A. & Matteucci , F. 2011, , 530, A98

  42. [50]

    Queiroz , A. B. A., Anders , F., Chiappini , C., et al. 2023, , 673, A155

  43. [51]

    M., Villata , M., & Navarro , J

    Raiteri , C. M., Villata , M., & Navarro , J. F. 1996, A & A, 315, 105

  44. [52]

    A., et al

    Recio-Blanco , A., de Laverny , P., Palicio , P. A., et al. 2023, , 674, A29

  45. [53]

    D., et al

    Rodr \' guez , S., Garcia Lambas , D., Padilla , N. D., et al. 2022, , 514, 6157

  46. [54]

    Rupke , D. S. N., Kewley , L. J., & Chien , L.-H. 2010, , 723, 1255

  47. [55]

    Salpeter , E. E. 1955, , 121, 161

  48. [56]

    B., White , S

    Scannapieco , C., Tissera , P. B., White , S. D. M., & Springel , V. 2005, MNRAS, 364, 552

  49. [57]

    B., White , S

    Scannapieco , C., Tissera , P. B., White , S. D. M., & Springel , V. 2006, MNRAS, 371, 1125

  50. [58]

    B., Lambas , D

    Sillero , E., Tissera , P. B., Lambas , D. G., & Michel-Dansac , L. 2017, , 472, 4404

  51. [59]

    2021, , 647, A73

    Spitoni , E., Verma , K., Silva Aguirre , V., et al. 2021, , 647, A73

  52. [60]

    B., Sillero , E., et al

    Tapia-Contreras , B., Tissera , P. B., Sillero , E., et al. 2025, , 700, A69

  53. [61]

    A., Monachesi , A., Gomez , F

    Tau , E. A., Monachesi , A., Gomez , F. A., et al. 2025, , 699, A93

  54. [62]

    1998, , 296, 119

    Thomas , D., Greggio , L., & Bender , R. 1998, , 296, 119

  55. [63]

    Tinsley , B. M. 1980, , 5, 287

  56. [64]

    B., Bignone , L., Gonzalez-Jara , J., et al

    Tissera , P. B., Bignone , L., Gonzalez-Jara , J., et al. 2025, , 697, A134

  57. [65]

    B., Pedrosa , S

    Tissera , P. B., Pedrosa , S. E., Sillero , E., & Vilchez , J. M. 2016, , 456, 2982

  58. [66]

    B., Scannapieco , C., Beers , T

    Tissera , P. B., Scannapieco , C., Beers , T. C., & Carollo , D. 2013, MNRAS, 432, 3391

  59. [67]

    B., White , S

    Tissera , P. B., White , S. D. M., & Scannapieco , C. 2012, MNRAS, 420, 255

  60. [68]

    2024, , 529, 2946

    Walsen , K., Jofr \'e , P., Buder , S., et al. 2024, , 529, 2946

  61. [69]

    White , S. D. M. & Frenk , C. S. 1991, , 379, 52

  62. [70]

    Wiersma , R. P. C., Schaye , J., & Smith , B. D. 2009, , 393, 99

  63. [71]

    M., Henriques , B., Thomas , P

    Yates , R. M., Henriques , B., Thomas , P. A., et al. 2013, , 435, 3500

  64. [72]

    M., Henriques , B

    Yates , R. M., Henriques , B. M. B., Fu , J., et al. 2021, , 503, 4474

  65. [73]

    Zhang , C., Li , Z., Hu , Z., & Krumholz , M. R. 2025, , 540, 3906

Pith tools

Reviewed July 12, 2026 · model on record in the stance chip above.